resolve_conversationMark a support-inbox conversation resolved (closed) and return the result. A write; idempotent — resolving an already-resolved conversation is a no-op. Resolve conversation_id via list_conversations first. Do it after you've replied and the ask is handled.
| Name | Required | Description | Default |
|---|---|---|---|
| conversation_id | Yes | Conversation id to resolve, from list_conversations (required). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds useful context beyond annotations by explaining idempotency: 'resolving an already-resolved conversation is a no-op' and noting it 'return[s] the result.' It also categorizes it as 'A write' which aligns with readOnlyHint=false. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three short sentences, each carrying distinct information: action, idempotency, and usage context. It front-loads the main purpose and avoids any filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, single-parameter mutation tool with strong annotations and schema coverage, the description is fairly complete. It covers behavior, input provenance, and sequencing, though the nature of 'the result' is unspecified (no output schema).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides a full description of conversation_id, covering 100% of parameters. The description repeats the source ('via list_conversations') but adds no new semantics beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb and resource: 'Mark a support-inbox conversation resolved (closed) and return the result.' It distinguishes the tool from siblings like reply_to_conversation by focusing on the closing action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear when-to-use guidance: 'Resolve conversation_id via list_conversations first. Do it after you've replied and the ask is handled.' It implies the tool is for the final step but doesn't explicitly mention alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have distinct purposes, but the high number (55) and similar prefixes like 'analyze_', 'list_', 'create_' could cause some confusion. However, detailed descriptions help agents differentiate.
Tool names follow a consistent verb_noun snake_case pattern (e.g., create_feature, list_tasks). Only minor exceptions like 'whoami' fit a predictable style.
55 tools is well above the typical range for a MCP server. Even for a comprehensive product OS, the count feels excessive and may overwhelm agents.
CRUD operations cover most entities, but missing delete tools (e.g., no delete_feature, delete_task) create minor gaps. Analytics and customer tools are thorough.